7.13.1. Query syntax — Groonga v14.0.9 documentation

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# 7.13.1. Query syntax

Query syntax is a syntax to specify search condition for common Web search form. It is similar to the syntax of Google’s search form. For example, `word1 word2` means that groonga searches records that contain both `word1` and `word2`. `word1 OR word2` means that groonga searches records that contain either `word1` or `word2`.

Query syntax consists of Conditional expression , Combined expression and Assignment expression. Normally Assignment expression can be ignored. Because Assignment expression is disabled in the query option of select. You can use it by specifying `ALLOW_UPDATE` to the query_flags option.

Conditional expression specifies an condition. Combined expression consists of one or more Conditional expression, Combined expression or Assignment expression. Assignment expression can assigns a value to a column.

## 7.13.1.1. Sample data

Here are a schema definition and sample data to show usage.

Execution example:

    table_create Entries TABLE_PAT_KEY ShortText
    # [[0,1337566253.89858,0.000355720520019531],true]
    column_create Entries content COLUMN_SCALAR Text
    # [[0,1337566253.89858,0.000355720520019531],true]
    column_create Entries n_likes COLUMN_SCALAR UInt32
    # [[0,1337566253.89858,0.000355720520019531],true]
    table_create Terms TABLE_PAT_KEY ShortText --default_tokenizer TokenBigram --normalizer NormalizerAuto
    # [[0,1337566253.89858,0.000355720520019531],true]
    column_create Terms entries_key_index COLUMN_INDEX|WITH_POSITION Entries _key
    # [[0,1337566253.89858,0.000355720520019531],true]
    column_create Terms entries_content_index COLUMN_INDEX|WITH_POSITION Entries content
    # [[0,1337566253.89858,0.000355720520019531],true]
    load --table Entries
    [
    {"_key":    "The first post!",
     "content": "Welcome! This is my first post!",
     "n_likes": 5},
    {"_key":    "Groonga",
     "content": "I started to use Groonga. It's very fast!",
     "n_likes": 10},
    {"_key":    "Mroonga",
     "content": "I also started to use Mroonga. It's also very fast! Really fast!",
     "n_likes": 15},
    {"_key":    "Good-bye Senna",
     "content": "I migrated all Senna system!",
     "n_likes": 3},
    {"_key":    "Good-bye Tritonn",
     "content": "I also migrated all Tritonn system!",
     "n_likes": 3}
    ]
    # [[0,1337566253.89858,0.000355720520019531],5]

There is a table, `Entries`, for blog entries. An entry has title, content and the number of likes for the entry. Title is key of `Entries`. Content is value of `Entries.content` column. The number of likes is value of `Entries.n_likes` column.

`Entries._key` column and `Entries.content` column are indexed using `TokenBigram` tokenizer. So both `Entries._key` and `Entries.content` are fulltext search ready.

OK. The schema and data for examples are ready.

## 7.13.1.2. Escape

There are special characters in query syntax. To use a special character as itself, it should be escaped by prepending `\`. For example, `"` is a special character. It is escaped as `\"`.

Here is a special character list:

- `[space]` (escaped as `[backslash][space]`) (You should substitute `[space]` with a white space character that is 0x20 in ASCII and `[backslash]` with `\\`.)

- `"` (escaped as `\"`)

- `(` (escaped as `\(`)

- `)` (escaped as `\)`)

- `\` (escaped as `\\`)

You can use quote instead of escape special characters except `\` (backslash). You need to use backslash for escaping backslash like `\\` in quote.

Quote syntax is `"..."`. You need escape `"` as `\"` in `"..."` quote syntax. For example, `You say "Hello Alice!"` can be quoted `"You say \"Hello Alice!\""`.

In addition `'...'` isn’t available in query syntax.

Note

There is an important point which you have to care. The `\` (backslash) character is interpreted by command line shell. So if you want to search `(` itself for example, you need to escape twice (`\\(`) in command line shell. The command line shell interprets `\\(` as `\(`, then pass such a literal to Groonga. Groonga regards `\(` as `(`, then search `(` itself from database. If you can’t do intended search by Groonga, confirm whether special character is escaped properly.

## 7.13.1.3. Conditional expression

Here is available conditional expression list.

### 7.13.1.3.1. Full text search condition

Its syntax is `keyword`.

`Full text search condition` specifies a full text search condition against the default match columns. Match columns are full text search target columns.

You should specify the default match columns for full text search. They can be specified by `--match_columns` option of select. If you don’t specify the default match columns, this conditional expression fails.

This conditional expression does full text search with `keyword`. `keyword` should not contain any spaces. If `keyword` contains a space such as `search keyword`, it means two full text search conditions; `search` and `keyword`. If you want to specifies a keyword that contains one or more spaces, you can use `phrase search condition` that is described below.

Here is a simple example:

Execution example:

    select Entries --match_columns content --query fast
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         2
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         2,
    #         "Groonga",
    #         "I started to use Groonga. It's very fast!",
    #         10
    #       ],
    #       [
    #         3,
    #         "Mroonga",
    #         "I also started to use Mroonga. It's also very fast! Really fast!",
    #         15
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that contain a word `fast` in `content` column value.

`content` column is the default match column.

### 7.13.1.3.2. Phrase search condition

Its syntax is `"search keyword"`.

`Phrase search condition` specifies a phrase search condition against the default match columns.

You should specify the default match columns for full text search. They can be specified by `--match_columns` option of select. If you don’t specify the default match columns, this conditional expression fails.

This conditional expression does phrase search with `search keyword`. Phrase search searches records that contain `search` and `keyword` and those terms are appeared in the same order and adjacent. Thus, `Put a search keyword in the form` is matched but `Search by the keyword` and `There is a keyword. Search by it!` aren’t matched.

Here is a simple example:

Execution example:

    select Entries --match_columns content --query '"I started"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         2,
    #         "Groonga",
    #         "I started to use Groonga. It's very fast!",
    #         10
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that contain a phrase `I started` in `content` column value. `I also started` isn’t matched because `I` and `started` aren’t adjacent.

`content` column is the default match column.

### 7.13.1.3.3. Full text search condition (with explicit match column)

Its syntax is `column:@keyword`.

It’s similar to `full text search condition` but it doesn’t require the default match columns. You need to specify match column for the full text search condition by `column:` instead of `--match_columns` option of select.

This condtional expression is useful when you want to use two or more full text search against different columns. The default match columns specified by `--match_columns` option can’t be specified multiple times. You need to specify the second match column by this conditional expression.

The different between `full text search condition` and `full text search condition (with explicit match column)` is whether advanced match columns are supported or not. `Full text search condition` supports advanced match columns but `full text search condition (with explicit match column)` isn’t supported. Advanced match columns has the following features:

- Weight is supported.

- Using multiple columns are supported.

- Using index column as a match column is supported.

See description of `--match_columns` option of select about them.

Here is a simple example:

Execution example:

    select Entries --query content:@fast
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         2
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         2,
    #         "Groonga",
    #         "I started to use Groonga. It's very fast!",
    #         10
    #       ],
    #       [
    #         3,
    #         "Mroonga",
    #         "I also started to use Mroonga. It's also very fast! Really fast!",
    #         15
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that contain a word `fast` in `content` column value.

### 7.13.1.3.4. Phrase search condition (with explicit match column)

Its syntax is `column:@"search keyword"`.

It’s similar to `phrase search condition` but it doesn’t require the default match columns. You need to specify match column for the phrase search condition by `column:` instead of `--match_columns` option of select.

The different between `phrase search condition` and `phrase search condition (with explicit match column)` is similar to between `full text search condition` and `full text search condition (with explicit match column)`. `Phrase search condition` supports advanced match columns but `phrase search condition (with explicit match column)` isn’t supported. See description of `full text search condition (with explicit match column)` about advanced match columns.

Here is a simple example:

Execution example:

    select Entries --query 'content:@"I started"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         2,
    #         "Groonga",
    #         "I started to use Groonga. It's very fast!",
    #         10
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that contain a phrase `I started` in `content` column value. `I also started` isn’t matched because `I` and `started` aren’t adjacent.

### 7.13.1.3.5. Prefix search condition

Its syntax is `column:^value` or `value*`.

This conditional expression does prefix search with `value`. Prefix search searches records that contain a word that starts with `value`.

You can use fast prefix search against a column. The column must be indexed and index table must be patricia trie table (`TABLE_PAT_KEY`) or double array trie table (`TABLE_DAT_KEY`). You can also use fast prefix search against `_key` pseudo column of patricia trie table or double array trie table. You don’t need to index `_key`.

Prefix search can be used with other table types but it causes all records scan. It’s not problem for small records but it spends more time for large records.

It doesn’t require the default match columns such as `full text search condition` and `phrase search condition`.

Here is a simple example:

Execution example:

    select Entries --query '_key:^Goo'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         2
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         4,
    #         "Good-bye Senna",
    #         "I migrated all Senna system!",
    #         3
    #       ],
    #       [
    #         5,
    #         "Good-bye Tritonn",
    #         "I also migrated all Tritonn system!",
    #         3
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that contain a word that starts with `Goo` in `_key` pseudo column value. `Good-bye Senna` and `Good-bye Tritonn` are matched with the expression.

### 7.13.1.3.6. Suffix search condition

Its syntax is `column:$value`.

This conditional expression does suffix search with `value`. Suffix search searches records that contain a word that ends with `value`.

You can use fast suffix search against a column. The column must be indexed and index table must be patricia trie table (`TABLE_PAT_KEY`) with `KEY_WITH_SIS` flag. You can also use fast suffix search against `_key` pseudo column of patricia trie table (`TABLE_PAT_KEY`) with `KEY_WITH_SIS` flag. You don’t need to index `_key`. We recommended that you use index column based fast suffix search instead of `_key` based fast suffix search. `_key` based fast suffix search returns automatically registered substrings. (TODO: write document about suffix search and link to it from here.)

Note

Fast suffix search can be used only for non-ASCII characters such as hiragana in Japanese. You cannot use fast suffix search for ASCII character.

Suffix search can be used with other table types or patricia trie table without `KEY_WITH_SIS` flag but it causes all records scan. It’s not problem for small records but it spends more time for large records.

It doesn’t require the default match columns such as `full text search condition` and `phrase search condition`.

Here is a simple example. It uses fast suffix search for hiragana in Japanese that is one of non-ASCII characters.

Execution example:

    table_create Titles TABLE_NO_KEY
    # [[0,1337566253.89858,0.000355720520019531],true]
    column_create Titles content COLUMN_SCALAR ShortText
    # [[0,1337566253.89858,0.000355720520019531],true]
    table_create SuffixSearchTerms TABLE_PAT_KEY|KEY_WITH_SIS ShortText
    # [[0,1337566253.89858,0.000355720520019531],true]
    column_create SuffixSearchTerms index COLUMN_INDEX Titles content
    # [[0,1337566253.89858,0.000355720520019531],true]
    load --table Titles
    [
    {"content": "ぐるんが"},
    {"content": "むるんが"},
    {"content": "せな"},
    {"content": "とりとん"}
    ]
    # [[0,1337566253.89858,0.000355720520019531],4]
    select Titles --query 'content:$んが'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         2
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         2,
    #         "むるんが"
    #       ],
    #       [
    #         1,
    #         "ぐるんが"
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that have value that ends with `んが` in `content` column value. `ぐるんが` and `むるんが` are matched with the expression.

### 7.13.1.3.7. Near search condition

Its syntax is `*N"token1 token2 ..."`.

This conditional expression does near search with `token1`, `token2` and `...`. Near search searches records that contain the all specified tokens and there are at most 10 tokens between them. For example, `*N"a b c"` matches `a 1 2 3 4 5 b 6 7 8 9 10 c` but doesn’t match `a 1 2 3 4 5 b 6 7 8 9 10 11 c`:

Execution example:

    table_create NearTokens TABLE_NO_KEY
    # [[0,1337566253.89858,0.000355720520019531],true]
    column_create NearTokens content COLUMN_SCALAR ShortText
    # [[0,1337566253.89858,0.000355720520019531],true]
    table_create NearTokenTerms TABLE_PAT_KEY ShortText \
      --default_tokenizer TokenNgram \
      --normalizer NormalizerNFKC130
    # [[0,1337566253.89858,0.000355720520019531],true]
    column_create NearTokenTerms index COLUMN_INDEX|WITH_POSITION \
      NearTokens content
    # [[0,1337566253.89858,0.000355720520019531],true]
    load --table NearTokens
    [
    {"content": "a 1 2 3 4 5 b 6 7 8 9 10 c"},
    {"content": "a 1 2 3 4 5 b 6 7 8 9 10 11 c"},
    {"content": "a 1 2 3 4 5 b 6 7 8 9 10 11 12 c"}
    ]
    # [[0,1337566253.89858,0.000355720520019531],3]
    select NearTokens --match_columns content --query '*N"a b c"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ]
    #     ]
    #   ]
    # ]

Note that you must specify `WITH_POSITION` to an index column that is used for near search. If you don’t specify `WITH_POSITION`, near search can’t count distance correctly.

You can customize the max interval of the given tokens (`10` by default) by specifying a number after `*N`. Here is an example that uses `2` as the max interval of the given tokens:

    *N2"..."

Here is an example to customize the max interval of the given tokens:

Execution example:

    select NearTokens --match_columns content --query '*N11"a b c"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         2
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ],
    #       [
    #         2,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 11 c"
    #       ]
    #     ]
    #   ]
    # ]

To be precious, you can specify a word instead of a token for near search. Because the passed text is tokenized before near search. A word consists of one or more tokens. If you specify a word, it may not work as you expected. For example, `*N"a1b2c3d"` matches both `a 1 b 2 c 3 d` and `a b c d 1 2 3`:

Execution example:

    load --table NearTokens
    [
    {"content": "groonga mroonga rroonga pgroonga"},
    {"content": "groonga rroonga pgroonga mroonga"}
    ]
    # [[0,1337566253.89858,0.000355720520019531],2]
    select NearTokens \
      --match_columns content \
      --query '*NP"\\\"groonga mroonga\\\" pgroonga"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         6,
    #         "groonga mroonga rroonga pgroonga"
    #       ]
    #     ]
    #   ]
    # ]

Because `*N"a1b2c3d"` equals to `*N"a 1 b 2 c 3 d"`.

If you want to specify words, Near phrase search condition is what you want.

Added in version 12.0.1: The max intervals of each token.

You can specify the max intervals of each token. The default is no limit. It means that all intervals of each token are valid as long as the max interval is satisfied.

Here is an example that use `2` for the max interval of the first interval and `4` for the max interval of the second interval:

    *N10,2|4"a b c"

`10` is the max interval.

`|` is the separator of the max intervals of each token.

This matches `a x b x x x c`. But this doesn’t match `a x x b c`, `a b x x x x c` and so on because the former has `3` interval for the first interval that is larger than `2` and the latter has `5` interval for the second interval that is later than `4`.

Here is an example that specifies the max intervals of each token:

Execution example:

    select NearTokens --match_columns content --query '*N11,5|5"a b c"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         3
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ],
    #       [
    #         5,
    #         "a b c d 1 2 3"
    #       ]
    #     ]
    #   ]
    # ]
    select NearTokens --match_columns content --query '*N11,5|6"a b c"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         4
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ],
    #       [
    #         2,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 11 c"
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ],
    #       [
    #         5,
    #         "a b c d 1 2 3"
    #       ]
    #     ]
    #   ]
    # ]

You can omit one or more intervals. Omitted intervals are treated as `-1`. It means that `*N11,5` equals `*N11,5|-1`. `-1` means that no limit.

Here is an example that omits an interval:

Execution example:

    select NearTokens --match_columns content --query '*N11,5"a b c"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         4
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ],
    #       [
    #         2,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 11 c"
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ],
    #       [
    #         5,
    #         "a b c d 1 2 3"
    #       ]
    #     ]
    #   ]
    # ]
    select NearTokens --match_columns content --query '*N11,5|-1"a b c"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         4
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ],
    #       [
    #         2,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 11 c"
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ],
    #       [
    #         5,
    #         "a b c d 1 2 3"
    #       ]
    #     ]
    #   ]
    # ]

You can specify extra intervals. They are just ignored:

Execution example:

    select NearTokens --match_columns content --query '*N11,5|5|1|1|1"a b c"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         3
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ],
    #       [
    #         5,
    #         "a b c d 1 2 3"
    #       ]
    #     ]
    #   ]
    # ]
    select NearTokens --match_columns content --query '*N11,5|5"a b c"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         3
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ],
    #       [
    #         5,
    #         "a b c d 1 2 3"
    #       ]
    #     ]
    #   ]
    # ]

### 7.13.1.3.8. Near phrase search condition

Its syntax is `*NP"phrase1 phrase2 ..."`.

This conditional expression does near phrase search with `phrase1`, `phrase2` and `...`. Near phrase search searches records that contain the all specified phrases and there are at most 10 tokens between them. For example, `*NP"a1b2c3d"` matches `a 1 b 2 c 3 d` but doesn’t match `a b c d 1 2 3`. Because the latter uses different order:

Execution example:

    select NearTokens --match_columns content --query '*NP"a1b2c3d"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ]
    #     ]
    #   ]
    # ]

You can use a phrase that includes spaces by quoting such as `*NP"\"groonga mroonga\" pgroonga"`. Note that you need to escape `\"` in command syntax such as `*NP"\\\"groonga mroonga\\\" pgroonga"`. This query matches `groonga mroonga pgroonga` but doesn’t match `groonga pgroonga mroonga` because `mroonga` isn’t right after `groonga`:

Execution example:

    load --table NearTokens
    [
    {"content": "groonga mroonga rroonga pgroonga"},
    {"content": "groonga rroonga pgroonga mroonga"}
    ]
    # [[0,1337566253.89858,0.000355720520019531],2]
    select NearTokens \
      --match_columns content \
      --query '*NP"\\\"groonga mroonga\\\" pgroonga"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         6,
    #         "groonga mroonga rroonga pgroonga"
    #       ]
    #     ]
    #   ]
    # ]

You can customize the max interval of the given phrases (`10` by default) by specifying a number after `*NP`. Here is an example that uses `2` as the max interval of the given phrases:

    *NP2"..."

Here is an example to customize the max interval of the given phrases:

Execution example:

    select NearTokens --match_columns content --query '*NP1"groonga pgroonga"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         7,
    #         "groonga rroonga pgroonga mroonga"
    #       ]
    #     ]
    #   ]
    # ]

You can use additional interval only for the last phrase. It means that you can accept more distance only between the second to last phrase and the last phrase. This is useful for implementing a near phrase search in the same sentence. If you specify `.` (sentence end phrase) as the last phrase and specify `-1` as the additional last interval, the other specified phrases must be appeared before `.`. You must append `$` to the last phrase like `.$`.

Here is an example that uses `-1` as the additional last interval of the given phrases:

    *NP10,-1"a b .$"

Here is an example to customize the additional last interval of the given phrases:

Execution example:

    load --table NearTokens
    [
    {"content": "x 1 y 2 3 4 . x 1 2 y 3 z 4 5 6 7 ."},
    {"content": "x 1 2 y 3 4 . x 1 2 y 3 z 4 5 6 7 ."},
    {"content": "x 1 2 3 y 4 . x 1 y 2 z 3 4 5 6 7 ."},
    ]
    # [[0,1337566253.89858,0.000355720520019531],3]
    select NearTokens --match_columns content --query '*NP2,-1"x y .$"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         3
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         8,
    #         "x 1 y 2 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ],
    #       [
    #         9,
    #         "x 1 2 y 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ],
    #       [
    #         10,
    #         "x 1 2 3 y 4 . x 1 y 2 z 3 4 5 6 7 ."
    #       ]
    #     ]
    #   ]
    # ]

You can also use positive number for the additional last interval. If you specify positive number as the additional last interval, all of the following conditions must be satisfied:

1. The interval between the first phrase and the second to last phrase is less than or equals to `the max interval`.

2. The interval between the first phrase and the last phrase is less than or equals to `the max interval` + `the additional last interval`.

If you specify negative number as the additional last interval, the second condition isn’t required. Appearing the last phrase is just needed.

Here is an example to use positive number as the additional last interval:

Execution example:

    select NearTokens --match_columns content --query '*NP2,4"x y .$"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         2
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         8,
    #         "x 1 y 2 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ],
    #       [
    #         9,
    #         "x 1 2 y 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ]
    #     ]
    #   ]
    # ]

Added in version 12.0.1: The max intervals of each phrase.

You can also specify the max intervals of each phrase like Near search condition.

Here is an example:

Execution example:

    select NearTokens --match_columns content --query '*NP11,0,5|5"a b c"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         3
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ],
    #       [
    #         5,
    #         "a b c d 1 2 3"
    #       ]
    #     ]
    #   ]
    # ]
    select NearTokens --match_columns content --query '*NP11,0,5|6"a b c"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         3
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ],
    #       [
    #         5,
    #         "a b c d 1 2 3"
    #       ]
    #     ]
    #   ]
    # ]

### 7.13.1.3.9. Near phrase product search condition

Added in version 11.1.1.

Its syntax is `*NPP"(phrase1_1 phrase1_2 ...) (phrase2_1 phrase2_2 ...) ..."`.

This conditional expression does multiple Near phrase search condition. Phrases for each Near phrase search condition are computed as product of `{phrase1_1, phrase1_2, ...}`, `{phrase2_1, phrase2_2, ...}` and `...`. For example, `*NPP"(a b c) (d e)"` uses the following phrases for near phrase searches:

- `a d`

- `a e`

- `b d`

- `b e`

- `c d`

- `c e`

Here is a simple example:

Execution example:

    select NearTokens --match_columns content --query '*NPP"(a x) (b y)"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         8
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ],
    #       [
    #         2,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 11 c"
    #       ],
    #       [
    #         3,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 11 12 c"
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ],
    #       [
    #         5,
    #         "a b c d 1 2 3"
    #       ],
    #       [
    #         8,
    #         "x 1 y 2 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ],
    #       [
    #         9,
    #         "x 1 2 y 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ],
    #       [
    #         10,
    #         "x 1 2 3 y 4 . x 1 y 2 z 3 4 5 6 7 ."
    #       ]
    #     ]
    #   ]
    # ]

You can use the all features of Near phrase search condition such as the max interval, `$` for the last phrase and the additional last interval.

Execution example:

    select NearTokens --match_columns content --query '*NPP2,-1"(a x) (b c y) (d$ .$)"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         5
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ],
    #       [
    #         5,
    #         "a b c d 1 2 3"
    #       ],
    #       [
    #         8,
    #         "x 1 y 2 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ],
    #       [
    #         9,
    #         "x 1 2 y 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ],
    #       [
    #         10,
    #         "x 1 2 3 y 4 . x 1 y 2 z 3 4 5 6 7 ."
    #       ]
    #     ]
    #   ]
    # ]

Added in version 12.0.1: The max intervals of each phrase.

You can also specify the max intervals of each phrase like Near search condition.

Here is an example:

Execution example:

    select NearTokens --match_columns content --query '*NPP11,0,5|5"(a x) (b y) (c z)"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         6
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ],
    #       [
    #         5,
    #         "a b c d 1 2 3"
    #       ],
    #       [
    #         8,
    #         "x 1 y 2 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ],
    #       [
    #         9,
    #         "x 1 2 y 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ],
    #       [
    #         10,
    #         "x 1 2 3 y 4 . x 1 y 2 z 3 4 5 6 7 ."
    #       ]
    #     ]
    #   ]
    # ]
    select NearTokens --match_columns content --query '*NPP11,0,5|6"(a x) (b y) (c z)"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         6
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ],
    #       [
    #         5,
    #         "a b c d 1 2 3"
    #       ],
    #       [
    #         8,
    #         "x 1 y 2 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ],
    #       [
    #         9,
    #         "x 1 2 y 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ],
    #       [
    #         10,
    #         "x 1 2 3 y 4 . x 1 y 2 z 3 4 5 6 7 ."
    #       ]
    #     ]
    #   ]
    # ]

This is more effective than multiple Near phrase search condition .

### 7.13.1.3.10. Ordered near phrase search condition

Added in version 11.0.9.

It’s syntax is `*ONP"phrase1 phrase2 ..."`

This conditional expression does ordered near phrase search with `phrase1`, `phrase2` and `...`. Ordered near phrase search is similar to Near phrase search condition but ordered near phrase search checks phrases order. For example, `*ONP"groonga mroonga pgroonga"` matches `groonga mroonga rroonga pgroonga` but doesn’t match `groonga rroonga pgroonga mroonga`. Because the latter uses different order:

Execution example:

    select NearTokens \
      --match_columns content \
      --query '*ONP"groonga mroonga pgroonga"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         6,
    #         "groonga mroonga rroonga pgroonga"
    #       ]
    #     ]
    #   ]
    # ]

You can use the all features of Near phrase search condition such as the max interval and the additional last interval. But you don’t need to specify `$` for the last phrase because the last phrase in query is the last phrase.

Added in version 12.0.1: The max intervals of each phrase.

You can also specify the max intervals of each phrase like Near search condition.

### 7.13.1.3.11. Ordered near phrase product search condition

Added in version 11.1.1.

Its syntax is `*ONPP"(phrase1_1 phrase1_2 ...) (phrase2_1 phrase2_2 ...) ..."`.

This conditional expression does ordered near phrase product search. Ordered near phrase product search is similar to Near phrase product search condition but ordered near phrase product search checks phrases order like Ordered near phrase search condition. For example, `*ONPP"(a b c) (d e)"` matches `a 1 d` but doesn’t match `d 1 a`. Because the latter uses different order.

Here is a simple example:

Execution example:

    select NearTokens \
      --match_columns content \
      --query '*ONPP"(a x) (b y)"'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         8
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "content",
    #           "ShortText"
    #         ]
    #       ],
    #       [
    #         1,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 c"
    #       ],
    #       [
    #         2,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 11 c"
    #       ],
    #       [
    #         3,
    #         "a 1 2 3 4 5 b 6 7 8 9 10 11 12 c"
    #       ],
    #       [
    #         4,
    #         "a 1 b 2 c 3 d"
    #       ],
    #       [
    #         5,
    #         "a b c d 1 2 3"
    #       ],
    #       [
    #         8,
    #         "x 1 y 2 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ],
    #       [
    #         9,
    #         "x 1 2 y 3 4 . x 1 2 y 3 z 4 5 6 7 ."
    #       ],
    #       [
    #         10,
    #         "x 1 2 3 y 4 . x 1 y 2 z 3 4 5 6 7 ."
    #       ]
    #     ]
    #   ]
    # ]

You can use the all features of Near phrase search condition such as the max interval and the additional last interval. But you don’t need to specify `$` for the last phrase because the last phrase in query is the last phrase.

Added in version 12.0.1: The max intervals of each phrase.

You can also specify the max intervals of each phrase like Near search condition.

### 7.13.1.3.12. Similar search condition

TODO

### 7.13.1.3.13. Equal condition

Its syntax is `column:value`.

It matches records that `column` value is equal to `value`.

It doesn’t require the default match columns such as `full text search condition` and `phrase search condition`.

Here is a simple example:

Execution example:

    select Entries --query _key:Groonga
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         2,
    #         "Groonga",
    #         "I started to use Groonga. It's very fast!",
    #         10
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that `_key` column value is equal to `Groonga`.

### 7.13.1.3.14. Not equal condition

Its syntax is `column:!value`.

It matches records that `column` value isn’t equal to `value`.

It doesn’t require the default match columns such as `full text search condition` and `phrase search condition`.

Here is a simple example:

Execution example:

    select Entries --query _key:!Groonga
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         4
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         4,
    #         "Good-bye Senna",
    #         "I migrated all Senna system!",
    #         3
    #       ],
    #       [
    #         5,
    #         "Good-bye Tritonn",
    #         "I also migrated all Tritonn system!",
    #         3
    #       ],
    #       [
    #         3,
    #         "Mroonga",
    #         "I also started to use Mroonga. It's also very fast! Really fast!",
    #         15
    #       ],
    #       [
    #         1,
    #         "The first post!",
    #         "Welcome! This is my first post!",
    #         5
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that `_key` column value is not equal to `Groonga`.

### 7.13.1.3.15. Less than condition

Its syntax is `column:<value`.

It matches records that `column` value is less than `value`.

If `column` type is numerical type such as `Int32`, `column` value and `value` are compared as number. If `column` type is text type such as `ShortText`, `column` value and `value` are compared as bit sequence.

It doesn’t require the default match columns such as `full text search condition` and `phrase search condition`.

Here is a simple example:

Execution example:

    select Entries --query n_likes:<10
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         3
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         4,
    #         "Good-bye Senna",
    #         "I migrated all Senna system!",
    #         3
    #       ],
    #       [
    #         5,
    #         "Good-bye Tritonn",
    #         "I also migrated all Tritonn system!",
    #         3
    #       ],
    #       [
    #         1,
    #         "The first post!",
    #         "Welcome! This is my first post!",
    #         5
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that `n_likes` column value is less than `10`.

### 7.13.1.3.16. Greater than condition

Its syntax is `column:>value`.

It matches records that `column` value is greater than `value`.

If `column` type is numerical type such as `Int32`, `column` value and `value` are compared as number. If `column` type is text type such as `ShortText`, `column` value and `value` are compared as bit sequence.

It doesn’t require the default match columns such as `full text search condition` and `phrase search condition`.

Here is a simple example:

Execution example:

    select Entries --query n_likes:>10
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         3,
    #         "Mroonga",
    #         "I also started to use Mroonga. It's also very fast! Really fast!",
    #         15
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that `n_likes` column value is greater than `10`.

### 7.13.1.3.17. Less than or equal to condition

Its syntax is `column:<=value`.

It matches records that `column` value is less than or equal to `value`.

If `column` type is numerical type such as `Int32`, `column` value and `value` are compared as number. If `column` type is text type such as `ShortText`, `column` value and `value` are compared as bit sequence.

It doesn’t require the default match columns such as `full text search condition` and `phrase search condition`.

Here is a simple example:

Execution example:

    select Entries --query n_likes:<=10
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         4
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         4,
    #         "Good-bye Senna",
    #         "I migrated all Senna system!",
    #         3
    #       ],
    #       [
    #         5,
    #         "Good-bye Tritonn",
    #         "I also migrated all Tritonn system!",
    #         3
    #       ],
    #       [
    #         2,
    #         "Groonga",
    #         "I started to use Groonga. It's very fast!",
    #         10
    #       ],
    #       [
    #         1,
    #         "The first post!",
    #         "Welcome! This is my first post!",
    #         5
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that `n_likes` column value is less than or equal to `10`.

### 7.13.1.3.18. Greater than or equal to condition

Its syntax is `column:>=value`.

It matches records that `column` value is greater than or equal to `value`.

If `column` type is numerical type such as `Int32`, `column` value and `value` are compared as number. If `column` type is text type such as `ShortText`, `column` value and `value` are compared as bit sequence.

It doesn’t require the default match columns such as `full text search condition` and `phrase search condition`.

Here is a simple example:

Execution example:

    select Entries --query n_likes:>=10
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         2
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         2,
    #         "Groonga",
    #         "I started to use Groonga. It's very fast!",
    #         10
    #       ],
    #       [
    #         3,
    #         "Mroonga",
    #         "I also started to use Mroonga. It's also very fast! Really fast!",
    #         15
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that `n_likes` column value is greater than or equal to `10`.

### 7.13.1.3.19. Regular expression condition

Added in version 5.0.1.

Its syntax is `column:~pattern`.

It matches records that `column` value is matched to `pattern`. `pattern` must be valid Regular expression.

The following example uses `.roonga` as pattern. It matches `Groonga`, `Mroonga` and so on.

Execution example:

    select Entries --query content:~.roonga
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         2
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         2,
    #         "Groonga",
    #         "I started to use Groonga. It's very fast!",
    #         10
    #       ],
    #       [
    #         3,
    #         "Mroonga",
    #         "I also started to use Mroonga. It's also very fast! Really fast!",
    #         15
    #       ]
    #     ]
    #   ]
    # ]

In most cases, regular expression is evaluated sequentially. So it may be slow against many records.

In some cases, Groonga evaluates regular expression by index. It’s very fast. See Regular expression for details.

## 7.13.1.4. Combined expression

Here is available combined expression list.

### 7.13.1.4.1. Logical OR

Its syntax is `a OR b`.

`a` and `b` are conditional expressions, conbinded expressions or assignment expressions.

If at least one of `a` and `b` are matched, `a OR b` is matched.

Here is a simple example:

Execution example:

    select Entries --query 'n_likes:>10 OR content:@senna'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         2
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         3,
    #         "Mroonga",
    #         "I also started to use Mroonga. It's also very fast! Really fast!",
    #         15
    #       ],
    #       [
    #         4,
    #         "Good-bye Senna",
    #         "I migrated all Senna system!",
    #         3
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that `n_likes` column value is greater than `10` or contain a word `senna` in `content` column value.

### 7.13.1.4.2. Logical AND

Its syntax is `a + b` or just `a b`.

`a` and `b` are conditional expressions, conbinded expressions or assignment expressions.

If both `a` and `b` are matched, `a + b` is matched.

You can specify `+` the first expression such as `+a`. The `+` is just ignored.

Here is a simple example:

Execution example:

    select Entries --query 'n_likes:>=10 + content:@groonga'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         2,
    #         "Groonga",
    #         "I started to use Groonga. It's very fast!",
    #         10
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that `n_likes` column value is greater than or equal to `10` and contain a word `groonga` in `content` column value.

### 7.13.1.4.3. Logical AND NOT

Its syntax is `a - b`.

`a` and `b` are conditional expressions, conbinded expressions or assignment expressions.

If `a` is matched and `b` is not matched, `a - b` is matched.

You can not specify `-` the first expression such as `-a`. It’s syntax error.

Here is a simple example:

Execution example:

    select Entries --query 'n_likes:>=10 - content:@groonga'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         3,
    #         "Mroonga",
    #         "I also started to use Mroonga. It's also very fast! Really fast!",
    #         15
    #       ]
    #     ]
    #   ]
    # ]

The expression matches records that `n_likes` column value is greater than or equal to `10` and don’t contain a word `groonga` in `content` column value.

### 7.13.1.4.4. Grouping

Its syntax is `(...)`. `...` is space separated expression list.

`(...)` groups one ore more expressions and they can be processed as an expression. `a b OR c` means that `a` and `b` are matched or `c` is matched. `a (b OR c)` means that `a` and one of `b` and `c` are matched.

Here is a simple example:

Execution example:

    select Entries --query 'n_likes:<5 content:@senna OR content:@fast'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         3
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         4,
    #         "Good-bye Senna",
    #         "I migrated all Senna system!",
    #         3
    #       ],
    #       [
    #         2,
    #         "Groonga",
    #         "I started to use Groonga. It's very fast!",
    #         10
    #       ],
    #       [
    #         3,
    #         "Mroonga",
    #         "I also started to use Mroonga. It's also very fast! Really fast!",
    #         15
    #       ]
    #     ]
    #   ]
    # ]
    select Entries --query 'n_likes:<5 (content:@senna OR content:@fast)'
    # [
    #   [
    #     0,
    #     1337566253.89858,
    #     0.000355720520019531
    #   ],
    #   [
    #     [
    #       [
    #         1
    #       ],
    #       [
    #         [
    #           "_id",
    #           "UInt32"
    #         ],
    #         [
    #           "_key",
    #           "ShortText"
    #         ],
    #         [
    #           "content",
    #           "Text"
    #         ],
    #         [
    #           "n_likes",
    #           "UInt32"
    #         ]
    #       ],
    #       [
    #         4,
    #         "Good-bye Senna",
    #         "I migrated all Senna system!",
    #         3
    #       ]
    #     ]
    #   ]
    # ]

The first expression doesn’t use grouping. It matches records that `n_likes:<5` and `content:@senna` are matched or `content:@fast` is matched.

The second expression uses grouping. It matches records that `n_likes:<5` and one of `content:@senna` or `content:@fast` are matched.

## 7.13.1.5. Assignment expression

This section is for advanced users. Because assignment expression is disabled in `--query` option of select by default. You need to specify `ALLOW_COLUMN|ALLOW_UPDATE` as `--query_flags` option value to enable assignment expression.

Assignment expression in query syntax has some limitations. So you should use Script syntax instead of query syntax for assignment.

There is only one syntax for assignment expression. It’s `column:=value`.

`value` is assigend to `column`. `value` is always processed as string in query syntax. `value` is casted to the type of `column` automatically. It causes some limitations. For example, you cannot use boolean literal such as `true` and `false` for `Bool` type column. You need to use empty string for `false` but query syntax doesn’t support `column:=` syntax.

See Cast about cast.